Blar i forfatter "Senthilkumaran, Paramasivam"

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    • Deep learning architecture “LightOCT” for diagnostic decision support using optical coherence tomography images of biological samples 

      Butola, Ankit; Prasad, Dilip Kumar; Ahmad, Azeem; Dubey, Vishesh Kumar; Qaiser, Darakhshan; Srivastava, Anurag; Senthilkumaran, Paramasivam; Ahluwalia, Balpreet Singh; Mehta, Dalip Singh (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-08-13)
      Optical coherence tomography (OCT) is being increasingly adopted as a label-free and non-invasive technique for biomedical applications such as cancer and ocular disease diagnosis. Diagnostic information for these tissues is manifest in textural and geometric features of the OCT images, which are used by human expertise to interpret and triage. However, it suffers delays due to the long process of ...

    • High space-bandwidth in quantitative phase imaging using partially spatially coherent digital holographic microscopy and a deep neural network 

      Butola, Ankit; Kanade, Sheetal Raosaheb; Bhatt, Sunil; Dubey, Vishesh Kumar; Kumar, Anand; Ahmad, Azeem; Prasad, Dilip K.; Senthilkumaran, Paramasivam; Ahluwalia, Balpreet Singh; Mehta, Dalip Singh (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-16)
      Quantitative phase microscopy (QPM) is a label-free technique that enables monitoring of morphological changes at the subcellular level. The performance of the QPM system in terms of spatial sensitivity and resolution depends on the coherence properties of the light source and the numerical aperture (NA) of objective lenses. Here, we propose high space-bandwidth quantitative phase imaging using ...